Virus evolutionary genetic algorithm for task collaboration of logistics distribution

Fanghua Ning; Zichen Chen; Li Xiong

doi:10.1117/12.664555

2 May 2006 Virus evolutionary genetic algorithm for task collaboration of logistics distribution

Fanghua Ning, Zichen Chen, Li Xiong

Proceedings Volume 6042, ICMIT 2005: Control Systems and Robotics; 60420N (2006) https://doi.org/10.1117/12.664555
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

In order to achieve JIT (Just-In-Time) level and clients' maximum satisfaction in logistics collaboration, a Virus Evolutionary Genetic Algorithm (VEGA) was put forward under double constraints of logistics resource and operation sequence. Based on mathematic description of a multiple objective function, the algorithm was designed to schedule logistics tasks with different due dates and allocate them to network members. By introducing a penalty item, make span and customers' satisfaction were expressed in fitness function. And a dynamic adaptive probability of infection was used to improve performance of local search. Compared to standard Genetic Algorithm (GA), experimental result illustrates the performance superiority of VEGA. So the VEGA can provide a powerful decision-making technique for optimizing resource configuration in logistics network.

Citation Download Citation

Fanghua Ning, Zichen Chen, and Li Xiong "Virus evolutionary genetic algorithm for task collaboration of logistics distribution", Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60420N (2 May 2006); https://doi.org/10.1117/12.664555

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